New York, October 29th / PRNewswire / -- AI and cloud cost optimization partner CloudKeeper today announced the launch of Full Stack FinOps for AI. This platform is designed to help enterprises track AI related expenses across models, applications, software licenses, and cloud infrastructure.

As enterprises adopt AI across different functions, their expenditures may be spread across multiple model providers, applications, teams, and infrastructure environments. When usage and expenses are recorded in separate systems, it becomes quite challenging to understand the total cost of these deployments.

Full Stack FinOps for AI integrates these cost elements through a unified dashboard, providing visualization of key areas of expenditure for AI, including:

• AI Inference and model costs: Tracking expenditures for AI models, providers, workloads, and applications.
• AI License Costs: View software licenses, providers, teams, and related expenses.
• AI Infrastructure Costs: Understand cloud infrastructure costs related to the workload of AI.
• Token Usage Analysis: Monitoring the token consumption and expenditure patterns of different AI models.
• GPU Cost and Utilization Analysis: View the usage of GPU, infrastructure costs, and potential idle situations.
• Multi-cloud dashboard: Integrates cost and usage data from AWS, Microsoft Azure, and Google Cloud.

The platform also supports the model context protocol ( MCP ), enabling enterprises to connect their own large language models ( LLM ) and obtain cost insights and recommendations ( AI ) within existing ( AI ) workflows.

CloudKeeper CEO Deepak Mittal stated: "Enterprises need to have a clear understanding of their own AI expenditures in order to make more confident decisions regarding how to adopt and expand AI. With the help of Full Stack FinOps for AI, we aim to help them integrate all cost insights into one view, understand their expenditure situations, and make more informed decisions regarding AI investments."

CloudKeeper Chief Product and Technology Officer Sanjeev Mittal stated: "The costs of AI / LLM do not only include the models and token usage. Software licenses, GPU, and cloud infrastructure that support the AI workload also contribute to the overall cost. By integrating these elements, the platform helps teams to examine their AI expenditures within context. MCP support also enables them to gain cost insights within their existing AI environment."

Enterprises can try out the platform for free for 30 days.

Start your 30-day free trial: Full Stack FinOps for AI

About CloudKeeper

CloudKeeper is a result-oriented AI and cloud cost optimization partner that combines the professional capabilities of FinOps, its own technology, and practical execution to help enterprises improve cost efficiency in their cloud and AI environments. With over 15 years of experience in cloud cost optimization, CloudKeeper has assisted more than 400 global companies in reducing their cloud and AI expenditures by an average of 20% on AWS, Microsoft Azure, and Google Cloud. Its pay-per-result model enables continuous cost savings without the need for upfront costs or long-term commitments.

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